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example.py
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example.py
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import time
import re
import numpy as np
from colonyModule.Node import Node
from colonyModule.Colony import Colony
def read_dataset(path):
dataset = open(path, "r")
i = 0
while True:
line = dataset.readline()
if not line:
break
if(i == 0):
n_nodes = int(line)
costs = {(i, j): 0 for i in range(n_nodes) for j in range(n_nodes)}
elif(i == 1):
demand = [int(q) for q in line.split()]
elif(i == 2):
capacity_vehicles = int(line)
else:
j = 0
for el in line.split():
costs[(i-3, j)] = float(el)
j = j+1
i = i+1
dataset.close()
return (n_nodes, costs, demand, capacity_vehicles)
def test_datasets(datasets, colony_size, alpha, beta, gamma, lam, rho, sigma, iterations):
solutions = []
for dataset in datasets:
n_nodes, cost_dict, demand, max_load = read_dataset(dataset["file"])
nodes = []
for i in range(n_nodes):
nodes.extend([Node(i)])
def cost_function(from_node, to_node):
return cost_dict[(from_node.id, to_node.id)]
cost_matrix = np.array(list(cost_dict.values())).reshape(n_nodes, n_nodes)
try:
colony = Colony(nodes, demand, nodes[0], max_load, colony_size, alpha, beta,
gamma, lam, rho, sigma, iterations, cost_function, None, cost_matrix)
start = time.time()
solution = colony.foraging()
end = time.time()
datasetName = re.sub(r"\/.*\/", "", dataset["file"])
solution["dataset"] = datasetName
solution["time"] = round(end-start, 2)
solution["gap"] = round(
(((solution["cost"]/dataset["best"])-1)*100), 2)
solution["route"] = [node.id for route in solution["route"]
for node in route]
solutions.append(solution)
print(datasetName + " ok")
except IndexError as e:
print(datasetName + " no", e)
return solutions
if __name__ == "__main__":
datasets = [{"file": "dataset/parma5.txt", "best": 19500},
{"file": "dataset/bergamo5.txt", "best": 7900},
{"file": "dataset/parma8.txt", "best": 22700},
{"file": "dataset/bergamo8.txt", "best": 10400},
{"file": "dataset/parma9.txt", "best": 23400},
{"file": "dataset/bergamo9.txt", "best": 10200},
{"file": "dataset/parma10.txt", "best": 25400},
{"file": "dataset/bergamo10.txt", "best": 10800}]
datasets += [{"file": "dataset/1Bari30.txt", "best": 14600},
{"file": "dataset/2Bari20.txt", "best": 15700},
{"file": "dataset/3Bari10.txt", "best": 20600},
{"file": "dataset/4ReggioEmilia30.txt", "best": 16900},
{"file": "dataset/5ReggioEmilia20.txt", "best": 23200},
{"file": "dataset/6ReggioEmilia10.txt", "best": 32500},
{"file": "dataset/7Bergamo30.txt", "best": 12600},
{"file": "dataset/8Bergamo20.txt", "best": 12700},
{"file": "dataset/9Bergamo12.txt", "best": 13500},
{"file": "dataset/10Parma30.txt", "best": 29000},
{"file": "dataset/11Parma20.txt", "best": 29000},
{"file": "dataset/12Parma10.txt", "best": 32500},
{"file": "dataset/13Treviso30.txt", "best": 29259},
{"file": "dataset/14Treviso20.txt", "best": 29259},
{"file": "dataset/15Treviso10.txt", "best": 31443},
{"file": "dataset/16LaSpezia30.txt", "best": 20746},
{"file": "dataset/17LaSpezia20.txt", "best": 20746},
{"file": "dataset/18LaSpezia10.txt", "best": 22811},
{"file": "dataset/19BuenosAires30.txt", "best": 76999},
{"file": "dataset/20BuenosAires20.txt", "best": 91619},
{"file": "dataset/21Ottawa30.txt", "best": 16202},
{"file": "dataset/22Ottawa20.txt", "best": 16202},
{"file": "dataset/23Ottawa10.txt", "best": 17576}]
solutions = test_datasets(datasets, colony_size=50, alpha=6,
beta=5, gamma=5, lam=5, rho=0.4, sigma=1, iterations=100)
print("\n")
for solution in solutions:
print(solution["dataset"], solution["cost"],
solution["time"], solution["gap"])